Stock Analytics MCP Server

The Stock Analytics MCP Server bridges the gap between AI assistants and real‑time market data by exposing Yahoo Finance as a structured resource within the Model Context Protocol. Developers who build conversational agents can now query live stock prices, historical trends, and company fundamentals without writing custom API wrappers or handling authentication themselves. By turning financial data into a first‑class MCP resource, the server lets AI models ask questions like “What was Apple’s closing price on 2023‑04‑15?” or “Show me the trend of Tesla’s revenue over the past five years.” and receive neatly formatted answers instantly.

At its core, the server implements a single resource endpoint that accepts standard MCP queries. When an AI client requests data for a ticker symbol, the server forwards the request to Yahoo Finance’s public endpoints, normalises the JSON response, and returns it in a consistent format. This abstraction removes the need for developers to manage rate limits or API keys, as Yahoo Finance’s data is freely accessible. The server also supports optional caching and pagination, ensuring that repeated queries are served quickly while respecting external rate constraints.

Key capabilities include:

• Dynamic ticker lookup – Resolve company names or symbols on the fly, allowing natural language queries.
• Historical price and volume data – Retrieve daily OHLCV values for arbitrary date ranges.
• Financial metrics extraction – Access key ratios, earnings reports, and balance sheet figures.
• Real‑time quote streaming – Optional WebSocket support for live price updates (if enabled).
• Metadata enrichment – Provide company descriptions, sector classifications, and market cap information.

Real‑world scenarios that benefit from this server are abundant. A portfolio management chatbot can pull current holdings and suggest rebalancing actions; a financial research assistant can generate comparative charts for multiple tickers; an educational agent can walk students through the mechanics of a stock split using live data. Because the server speaks MCP, any AI platform that understands the protocol—Claude, Gemini, or custom models—can integrate these capabilities with minimal friction.

What sets the Stock Analytics MCP Server apart is its simplicity and transparency. By leveraging Yahoo Finance’s public API, it avoids costly subscriptions while still delivering comprehensive market data. The server’s design encourages rapid iteration: developers can extend the resource with additional endpoints (e.g., options chains or macroeconomic indicators) without altering the MCP contract. This modularity, combined with native support for caching and pagination, makes it a powerful tool in any AI‑driven finance workflow.